Embedded System Design for Automotive Applications

Sangiovanni-Vincentelli, A.; Natale, Marco Di

doi:10.1109/mc.2007.344

Cited by 145 publications

(68 citation statements)

References 15 publications

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“…High-assurance control software for cyber physical systems has received much attention recently (e.g., [32,3,24,23,22,10,12]). Focusing on robust controller implementation, [32] and [22] provide simulation-based robustness analysis tools, while [3,24,10,12] studies issues related to fixed-point controller design.…”

Section: Related Workmentioning

confidence: 99%

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Automatic Verification of Finite Precision Implementations of Linear Controllers

Park

Pajić

Sokolsky

et al. 2017

Tools and Algorithms for the Construction and Analysis of Systems

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We consider the problem of verifying finite precision implementation of linear time-invariant controllers against mathematical specifications. A specification may have multiple correct implementations which are different from each other in controller state representation, but equivalent from a perspective of input-output behavior (e.g., due to optimization in a code generator). The implementations may use finite precision computations (e.g. floating-point arithmetic) which cause quantization (i.e., roundoff) errors. To address these challenges, we first extract a controller's mathematical model from the implementation via symbolic execution and floating-point error analysis, and then check approximate input-output equivalence between the extracted model and the specification by similarity checking. We show how to automatically verify the correctness of floating-point controller implementation in C language using the combination of techniques such as symbolic execution and convex optimization problem solving. We demonstrate the scalability of our approach through evaluation with randomly generated controller specifications of realistic size. Disciplines Computer Engineering | Computer Sciences AbstractWe consider the problem of verifying finite precision implementation of linear time-invariant controllers against mathematical specifications. A specification may have multiple correct implementations which are different from each other in controller state representation, but equivalent from a perspective of input-output behavior (e.g., due to optimization in a code generator). The implementations may use finite precision computations (e.g. floating-point arithmetic) which cause quantization (i.e., roundoff) errors. To address these challenges, we first extract a controller's mathematical model from the implementation via symbolic execution and floating-point error analysis, and then check approximate input-output equivalence between the extracted model and the specification by similarity checking. We show how to automatically verify the correctness of floating-point controller implementation in C language using the combination of techniques such as symbolic execution and convex optimization problem solving. We demonstrate the scalability of our approach through evaluation with randomly generated controller specifications of realistic size.

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Section: Related Workmentioning

confidence: 99%

“…Focusing on robust controller implementation, [32] and [22] provide simulation-based robustness analysis tools, while [3,24,10,12] studies issues related to fixed-point controller design. [4] presents a theorem proving method to verify the control related properties of Simulink models.…”

Section: Related Workmentioning

confidence: 99%

Automatic Verification of Finite Precision Implementations of Linear Controllers

Park

Pajić

Sokolsky

et al. 2017

Tools and Algorithms for the Construction and Analysis of Systems

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“…RTOS is used here to assign the priorities. Application code designed on an RTOS [11] can be quite diverse, ranging from a simple application for a digital stopwatch to a much more complex application for aircraft navigation [10]. Here Micro C/OS II is used to assign the priorities [5].…”

Section: Introductionmentioning

confidence: 99%

An RTOS based Industrial Wireless Sensor Network using Multiprocessor Support

Bavani¹,

Thomas²

2015

IJCA

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RTOS (Real Time Operating System) is a Process which is done between hardware and application in order to provide time constraints. Each industry has their own priority among the various tasks according to their process. RTOS is used here to assign the priorities. The values obtained in plant have to be transmitted to the control room. These values are sent in the form of packets. Packets have to be sent at particular time. During the packets transmission some collision may occur. To overcome this collision wireless HART (Highway Addressable Remote Transducer) is used. This project is implemented in two sections as prototype. First one runs with RTOS and LPC2148 as master node and another as normal data acquisition node to which sensors are connected. Second section contains a controller as per the need. Communications between two nodes are accomplished through wireless HART. The basic view of this technique is to reduce the possibility of collision (and thus increase the communication reliability), and to meet the critical requirement of industrial applications. This is essential to increase the communication reliability, and to meet the requirement of timing determinism of industrial applications. To do this, all the nodes must be synchronized precisely. Also, the stack designer must guarantee that the node can finish everything within the time slot. It offers benefits in terms of platform independency, product life cycle, safety and security, system integration complexity, and performance scalability. General TermsRTOS, Micro Controller OS, Wireless Hart, Multiprocessor system.

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“…Being aware that priority-based scheduling can lead to discontinuous behavior in time and timing anomalies [2], timing isolation in software execution is required to protect safety-critical embedded systems from timing faults.…”

Section: Introductionmentioning

confidence: 99%